MOSEK is a tool for solving mathematical optimization problems such as: linear programs, quadratic programs, conic problems, mixed integer problems. The MOSEK optimization software is designed to solve large-scale mathematical optimization problems. MOSEK main features are listed below. For additional questions, contact our support or browse the online documentation.
Problem types MOSEK can solve - Linear - Conic quadratic - Semidefinite (Positive semidefinite matrix variables) - Quadratic and quadratically constrained - General convex nonlinear - Mixed integer linear, conic and quadratic
Technical highlights - Problem size limited only by the available memory. - Interior-point optimizer with basis identification. - Primal and dual simplex optimizers for linear programming. - Highly efficient presolver for reducing problem size before optimization. - Network-simplex for problems with network flow structure. - Branch&bound&cut algorithm for mixed integer problems.
Strengths of MOSEK The strong point of MOSEK is its state-of-the-art interior-point optimizer for continous linear, quadratic and conic problems.
Parallel capabilities The interior-point optimizer is capable of exploiting multiple CPUs/cores. A concurrent optimizer is available that makes it possible to solve one problem with different optimizers simultaneously. The default mixed integer optimizer is parallelized and is run-to-run deterministic.
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